Cheat Sheets for Data Visualization Techniques

This paper introduces the concept of 'cheat sheets' for data visualization techniques, a set of concise graphical explanations and textual annotations inspired by infographics, data comics, and cheat sheets in other domains. Cheat sheets aim to address the increasing need for accessible material that supports a wide audience in understanding data visualization techniques, their use, their fallacies and so forth. We have carried out an iterative design process with practitioners, teachers and students of data science and visualization, resulting six types of cheat sheet (anatomy, construction, visual patterns, pitfalls, false-friends and well-known relatives) for six types of visualization, and formats for presentation. We assess these with a qualitative user study using 11 participants that demonstrates the readability and usefulness of our cheat sheets.

[1]  Thomas N. Dorsel,et al.  The Cheat-Sheet: Efficient Coding Device or Indispensable Crutch?. , 1979 .

[2]  M. Monmonier How to Lie with Maps , 1991 .

[3]  Larry Gonick,et al.  Cartoon Guide to Statistics , 1993 .

[4]  Valerie J. Bristor,et al.  Linking the Language Arts and Content Areas through Visual Technology , 1994 .

[5]  Gerald E. Jones How to Lie with Charts , 1995 .

[6]  Dylgg,et al.  Guidelines for Designing Information Visualization Applications , 1999 .

[7]  Randall Munroe Thing Explainer: Complicated Stuff in Simple Words , 2001 .

[8]  Yoav Wachsman,et al.  Should Cheat Sheets be Used as Study Aids in Economics Tests , 2002 .

[9]  Milo Schield,et al.  Information Literacy, Statistical Literacy and Data Literacy , 2004 .

[10]  R. Grossman,et al.  Graph-theoretic scagnostics , 2005, IEEE Symposium on Information Visualization, 2005. INFOVIS 2005..

[11]  Mick McGee,et al.  The Rapid Iterative Test and Evaluation Method: Better Products in Less Time , 2005 .

[12]  Milo Shields,et al.  Information Literacy, Statistical Literacy, Data Literacy , 2005 .

[13]  Jean-Daniel Fekete,et al.  MatrixExplorer: a Dual-Representation System to Explore Social Networks , 2006, IEEE Transactions on Visualization and Computer Graphics.

[14]  Mark Bailey,et al.  The Grammar of Graphics , 2007, Technometrics.

[15]  Brigitte Mach Erbe,et al.  Reducing Test Anxiety While Increasing Learning: The Cheat Sheet , 2007 .

[16]  Yeung-Nan Shieh,et al.  Fine arts in Solow model: a clarification , 2008 .

[17]  Jeffrey Heer,et al.  Sizing the horizon: the effects of chart size and layering on the graphical perception of time series visualizations , 2009, CHI.

[18]  Jacques Bertin,et al.  Semiology of Graphics - Diagrams, Networks, Maps , 2010 .

[19]  Christopher A. Brooks,et al.  Useful junk?: the effects of visual embellishment on comprehension and memorability of charts , 2010, CHI.

[20]  Lisa Stryjewski,et al.  40 years of boxplots , 2010 .

[21]  Alexander Repenning,et al.  Using scalable game design to teach computer science from middle school to graduate school , 2010, ITiCSE '10.

[22]  Alberto Cairo,et al.  The Functional Art: An introduction to information graphics and visualization , 2012 .

[23]  Jean-Daniel Fekete,et al.  A Principled Way of Assessing Visualization Literacy , 2014, IEEE Transactions on Visualization and Computer Graphics.

[24]  Jean-Daniel Fekete,et al.  Visualizing dynamic networks with matrix cubes , 2014, CHI.

[25]  Tamara Munzner,et al.  Visualization Analysis and Design , 2014, A.K. Peters visualization series.

[26]  Zhenpeng Zhao,et al.  Data Comics: Sequential Art for Data-Driven Storytelling , 2015 .

[27]  Yang Song,et al.  A quantitative case study in engineering of the efficacy of quality cheat-sheets , 2015, 2015 IEEE Frontiers in Education Conference (FIE).

[28]  Oded Nov,et al.  How Deceptive are Deceptive Visualizations?: An Empirical Analysis of Common Distortion Techniques , 2015, CHI.

[29]  Klaus Mueller,et al.  Learning Visualizations by Analogy: Promoting Visual Literacy through Visualization Morphing , 2015, IEEE Transactions on Visualization and Computer Graphics.

[30]  Dubravka Svetina,et al.  Research and Teaching: Data Visualization Literacy: Investigating Data Interpretation along the Novice-Expert Continuum. , 2015 .

[31]  Steven Franconeri,et al.  The Connected Scatterplot for Presenting Paired Time Series , 2016, IEEE Transactions on Visualization and Computer Graphics.

[32]  Jean-Daniel Fekete,et al.  Matrix Reordering Methods for Table and Network Visualization , 2016, Comput. Graph. Forum.

[33]  Jonathan C. Roberts,et al.  Sketching Designs Using the Five Design-Sheet Methodology , 2016, IEEE Transactions on Visualization and Computer Graphics.

[34]  Kyle Wm. Hall,et al.  Telling Stories about Dynamic Networks with Graph Comics , 2016, CHI.

[35]  Claudia López,et al.  Lessons Learned from Students' Cheat Sheets: Generic Models for Designing Programming Study Guides , 2016, 2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT).

[36]  Pierre Dragicevic,et al.  Time Curves: Folding Time to Visualize Patterns of Temporal Evolution in Data , 2016, IEEE Transactions on Visualization and Computer Graphics.

[37]  Katy Börner,et al.  Investigating aspects of data visualization literacy using 20 information visualizations and 273 science museum visitors , 2016, Inf. Vis..

[38]  Sung-Hee Kim,et al.  How do People Make Sense of Unfamiliar Visualizations?: A Grounded Model of Novice's Information Visualization Sensemaking , 2016, IEEE Transactions on Visualization and Computer Graphics.

[39]  Andy Kirk,et al.  Data Visualisation: A Handbook for Data Driven Design , 2016 .

[40]  Christophe Hurter,et al.  Towards Unambiguous Edge Bundling: Investigating Confluent Drawings for Network Visualization , 2017, IEEE Transactions on Visualization and Computer Graphics.

[41]  Kendall Nicholson,et al.  The Truthful Art: Data, Charts and Maps for Communication , 2017 .

[42]  M. Sheelagh T. Carpendale,et al.  The Emerging Genre of Data Comics , 2017, IEEE Computer Graphics and Applications.

[43]  Kim Marriott,et al.  Evaluating Perceptually Complementary Views for Network Exploration Tasks , 2017, CHI.

[44]  Bongshin Lee,et al.  Authoring Data-Driven Videos with DataClips , 2017, IEEE Transactions on Visualization and Computer Graphics.

[45]  Min Suk Chung,et al.  The use of educational comics in learning anatomy among multiple student groups , 2017, Anatomical sciences education.

[46]  Karrie Karahalios,et al.  Frames and Slants in Titles of Visualizations on Controversial Topics , 2018, CHI.

[47]  Matteo Farinella,et al.  The potential of comics in science communication , 2018 .

[48]  David Murray-Rust,et al.  Design Patterns for Data Comics , 2018, CHI.

[49]  Zhenpeng Zhao,et al.  Understanding Partitioning and Sequence in Data-Driven Storytelling , 2019, iConference.

[50]  David Murray-Rust,et al.  Comparing Effectiveness and Engagement of Data Comics and Infographics , 2019, CHI.

[51]  Zhen Li,et al.  Narvis: Authoring Narrative Slideshows for Introducing Data Visualization Designs , 2019, IEEE Transactions on Visualization and Computer Graphics.

[52]  A. Griffin Information Graphics , 2020, International Encyclopedia of Human Geography.